471 Model Deployment Jobs - Page 7

As a Python AI/ML Developer at the company, your main responsibilities will include: - Assisting in the development and implementation of machine learning models and algorithms. - Writing clean, efficient, and reusable Python code for data processing, modeling, and deployment. - Working on datasets by performing tasks such as data cleaning, preprocessing, feature engineering, and visualization. - Collaborating with senior data scientists and developers to build scalable ML solutions. - Conducting literature reviews and staying updated on the latest ML/AI research. - Contributing to model deployment and integration with APIs or web applications (basic knowledge is sufficient). The desired pro...

As a Machine Learning Operations (MLOps) Engineer at Neolytix working on US Healthcare Claims Management, your role will involve building, deploying, and maintaining AI/ML systems for the healthcare Revenue Cycle Management (RCM) platform. You will be responsible for operationalizing machine learning models to analyze claims, prioritize denials, and optimize revenue recovery through automated resolution pathways. **Key Responsibilities:** - Design and implement end-to-end ML pipelines for claims processing, including automated training, testing, and deployment workflows - Deploy and orchestrate LLMs and SLMs in production using containerization (Docker/Kubernetes) and Azure cloud services - ...

Role Overview: PharmaACE is a growing Global Healthcare Consulting Firm, headquartered in Princeton, New Jersey, with expert teams of Business Analysts across various locations. The firm provides Analytics and Business Solutions to a diverse clientele in the BioPharma sector, with expertise in Forecasting, Business Analytics, Competitive Intelligence, and more. They cater to clients in different therapeutic areas such as Oncology, Immuno-science, CNS, CV-Met, and Rare Diseases, across Primary Care, Specialty Care, and Hospital business units. Key Responsibilities: - Analyze different pharmaceutical/life sciences data sets including claims data, electronic medical records, patient level data,...

Job Description At Oracle Cloud Infrastructure (OCI), we're reimagining how enterprise cloud operations workand we want you to be part of it. OCI is a hyperscale cloud platform where operations are central to customer success. To scale and stay ahead, we're automating incident detection, diagnosis, and resolutionpushing the boundaries of AI and GenAI in cloud operations. As an ML Engineer, you'll design and build intelligent AI solutions that proactively manage cloud environments, enhance operational excellence, and deliver world-class customer experiences. If you're passionate about solving complex technical challenges and shaping the future of the autonomous cloud, this is your moment. Res...

Apply Here: https://zrec.in/PXeJO?source=CareerSite design, build, and deploy AI/ML and Generative AI solutions on Azure. Develop pipelines, productionize models, and collaborate with teams to deliver scalable enterprise AI use cases. Required Candidate profile Experienced Data Scientist skilled in Python, TF/PyTorch, Azure ML/OpenAI, LLMs & embeddings, vector DBs, MLOps with Docker/K8s, SQL, and end-to-end model deployment.

Job Responsibilities - Develop and implement advanced machine learning models to solve complex business problems, translating analytical findings into tangible business solutions. Develop computer vision algorithms and deploy them to production environments, ensuring seamless integration with existing systems and infrastructure. Understand business requirements by working closely with domain experts to define problem statements and success metrics that align with organizational goals. Collaborate with data engineers to design and implement efficient data pipelines that support model development, training, and deployment. Analyse large datasets to extract meaningful insights, identify pattern...

Job Responsibilities - Develop and implement advanced machine learning models to solve complex business problems, translating analytical findings into tangible business solutions. Develop computer vision algorithms and deploy them to production environments, ensuring seamless integration with existing systems and infrastructure. Understand business requirements by working closely with domain experts to define problem statements and success metrics that align with organizational goals. Collaborate with data engineers to design and implement efficient data pipelines that support model development, training, and deployment. Analyse large datasets to extract meaningful insights, identify pattern...

Job Responsibilities - Develop and implement advanced machine learning models to solve complex business problems, translating analytical findings into tangible business solutions. Develop computer vision algorithms and deploy them to production environments, ensuring seamless integration with existing systems and infrastructure. Understand business requirements by working closely with domain experts to define problem statements and success metrics that align with organizational goals. Collaborate with data engineers to design and implement efficient data pipelines that support model development, training, and deployment. Analyse large datasets to extract meaningful insights, identify pattern...

Role Overview: As the founding ML Scientist, you will be responsible for designing and deploying the core recommendation and personalisation systems that drive the matchmaking experience. Your role will involve owning the full lifecycle of these systems, from design to deployment, and establishing the groundwork for a scalable, real-time ranking infrastructure. Key Responsibilities: - Own and develop match-making, recommendation, ranking, and personalisation systems. - Work on creating a novel real-time adaptive matchmaking engine that learns from user interactions and other signals. - Design ranking and recommendation algorithms to tailor each user's feed for a curated experience. - Build u...

Overview We are seeking a Data scientist focusing on statistical modeling components, building classification, prediction, and optimization systems for the Claims Operations workflows . Responsibilities Develop classification and prediction models. Create pattern recognition systems for claims processing. Build optimization components for workflow efficiency. Implement evaluation metrics for model quality. Support user enablement and training. Assist with model documentation and knowledge transfer. Qualifications Develop classification and prediction models. Create pattern recognition systems for claims processing. Build optimization components for workflow efficiency. Implement evaluation m...

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains. 3 years of experience in a technical leadership role; overseeing projects. 2 years of experience in a people management, supervision/team leadership role. Preferred qualifications: Master's degree or PhD in Computer ...

You will be joining a team at EG dedicated to developing and maintaining an AI assistance solution for service and support. As an ML Ops / Cloud Engineer with 5 years of experience, your responsibilities will include designing, implementing, and managing the cloud infrastructure on AWS, deploying AI models at scale, and ensuring the operational excellence of our AI products based on AWS Large Language Models (LLMs). **Role Overview:** You will be a part of a newly set up team within the EG IT department, focused on supporting clients and employees with their daily activities. This team will closely cooperate with the ServiceNow team as the AI-based product will be integrated with ServiceNow ...

As a Data Scientist at our company, you will be responsible for supporting the development and deployment of machine learning models and analytics solutions aimed at improving decision-making across the mortgage lifecycle. Your key responsibilities will include: - Developing and maintaining machine learning models and statistical tools for various use cases such as risk scoring, churn prediction, segmentation, and document classification. - Collaborating with Product, Engineering, and Analytics teams to identify data-driven opportunities and support automation initiatives. - Translating business questions into modeling tasks and contributing to the design of experiments and success metrics. ...

As an Assistant Vice President (C12) in the TTS Analytics team at Citi, you will play a crucial role in leading a team of data scientists and analysts. Your responsibilities will include working on various data science projects throughout the year, focusing on business problems across the client life cycle such as acquisition, engagement, client experience, and retention within the TTS business. You will be expected to understand business needs, design, develop, and deploy machine learning models, and effectively communicate insights and recommendations to stakeholders. Key Responsibilities: - Lead a team of data scientists and analysts responsible for the full lifecycle of machine learning ...

As an AI Engineer at Sundew, your role will involve designing, building, and deploying AI-driven solutions, leveraging ML frameworks, programming expertise, and cloud platforms to drive innovation and deliver transformative value to global clients. Key Responsibilities: - Develop and deploy machine learning and deep learning models. - Collaborate with data engineers to prepare and optimize datasets. - Build scalable model training and inference pipelines. - Evaluate and fine-tune model performance. - Integrate AI solutions into products and internal systems. - Stay updated with the latest AI research and tools. Qualifications Required: - Proficiency in Python with ML libraries (TensorFlow, P...

Seeking an experienced Gen AI Architect with expertise in Generative AI, Azure OpenAI, AWS Bedrock, LangChain, and RAG. Responsible for architecting, fine-tuning, and deploying scalable AI/ML models. Required Candidate profile AI/ML professional (7–10 yrs) with hands-on experience in Generative AI, LLMs, LangChain, Azure OpenAI, Python, and PyTorch. Strong in model deployment, prompt engineering, and data pipelines.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Warsaw, Poland; Bengaluru, Karnataka, India . Minimum qualifications: Bachelor's degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 2 years of experience working with Generative AI, Vertex AI and Generative AI Agent. 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization ...

As a Solution Architect AI/ML at Space Inventive, you will be responsible for designing and delivering advanced architectures for AI and Generative AI applications. This role demands a blend of technical depth and architectural visionturning business requirements into scalable, secure, and high-performing AI solutions. You will play a key part in shaping solution blueprints, guiding development teams, and ensuring successful implementation of enterprise-grade AI applications. Architectural Design & Enterprise Solutions -Design and implement robust, scalable architectures for AI/ML applications, including LLMs, RAG pipelines, agentic orchestration, and vector databases with built-in guardrail...

Deploy and monitor ML models in production. Build CI/CD pipelines and manage infrastructure for scalable AI operations. •Deploy and monitor ML models •Build CI/CD pipelines for ML workflows •Manage model registries and feature stores •Ensure system reliability and automate retraining Must have- Docker/Kubernetes, GitHub/GitLab CI, MLflow, model deployment Good to have- AIOps tools, automation scripting, feature store management

Key Responsibilities: Machine Learning Model Development: Design, implement, and deploy machine learning models to address complex challenges in the insurance domain. Work on diverse projects, leveraging machine learning techniques to extract insights and drive business value. Machine Learning Pipelines: Design and implement ETL processes for Machine Learning to ensure accurate and timely data integration from multiple sources. Build and optimize end-to-end machine learning pipelines, ensuring scalability, efficiency, and maintainability. Collaborate with data engineers to integrate machine learning models into production systems. Artificial Intelligence: Apply knowledge and experience in wo...

Key Responsibilities: Machine Learning Model Development: Design, implement, and deploy machine learning models to address complex challenges in the insurance domain. Work on diverse projects, leveraging machine learning techniques to extract insights and drive business value. Machine Learning Pipelines: Design and implement ETL processes for Machine Learning to ensure accurate and timely data integration from multiple sources. Build and optimize end-to-end machine learning pipelines, ensuring scalability, efficiency, and maintainability. Collaborate with data engineers to integrate machine learning models into production systems. Artificial Intelligence: Apply knowledge and experience in wo...

Key Responsibilities: Machine Learning Model Development: Design, implement, and deploy machine learning models to address complex challenges in the insurance domain. Work on diverse projects, leveraging machine learning techniques to extract insights and drive business value. Machine Learning Pipelines: Design and implement ETL processes for Machine Learning to ensure accurate and timely data integration from multiple sources. Build and optimize end-to-end machine learning pipelines, ensuring scalability, efficiency, and maintainability. Collaborate with data engineers to integrate machine learning models into production systems. Artificial Intelligence: Apply knowledge and experience in wo...

Key Responsibilities: Machine Learning Model Development: Design, implement, and deploy machine learning models to address complex challenges in the insurance domain. Work on diverse projects, leveraging machine learning techniques to extract insights and drive business value. Machine Learning Pipelines: Design and implement ETL processes for Machine Learning to ensure accurate and timely data integration from multiple sources. Build and optimize end-to-end machine learning pipelines, ensuring scalability, efficiency, and maintainability. Collaborate with data engineers to integrate machine learning models into production systems. Artificial Intelligence: Apply knowledge and experience in wo...

Description We are seeking a talented GenAI Developer to join our team in India. The ideal candidate will have 3-10 years of experience in developing and implementing AI solutions, with a focus on generative models. You will work on innovative projects that leverage cutting-edge technologies to drive business value. Responsibilities Design, develop, and implement Generative AI models and solutions. Collaborate with cross-functional teams to gather requirements and define project scope. Conduct experiments to evaluate and optimize model performance. Stay updated with the latest advancements in AI and machine learning technologies. Document development processes, code, and test results for fut...

Preferred Qualifications: Experience in AI/ML in the healthcare sector Experience working with cross-functional and distributed teams in a global and diverse environment Experience in establishing AI/ML best practices, standards, RUAI, and ethics Required Qualifications: Proven solid Python programming skills and experience with deep learning popular frameworks such as PyTorch Proficiency in SQL and other programming languages for data analysis and modeling Proficiency with cloud development environments such as Azure, AWS, and GCP Proven in-depth knowledge in Generative AI technology and Large Language Models (LLM)Experience with LLM frameworks and/or NLP approaches such as text embedding E...